Source code for

# -*- coding: utf-8 -*-
# Copyright 2021 IRT Saint Exupéry,
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License version 3 as published by the Free Software Foundation.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# Lesser General Public License for more details.
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.

# Contributors:
#    INITIAL AUTHORS - initial API and implementation and/or initial
#                           documentation
#        :author: Matthias De Lozzo
r"""Draw a variable versus two others from a :class:`.Dataset`.

A :class:`.ZvsXY` plot represents the variable :math:`z` with respect to
:math:`x` and :math:`y` as a surface plot, based on a set of points
:points :math:`\{x_i,y_i,z_i\}_{1\leq i \leq n}`. This interpolation is
relies on the Delaunay triangulation of :math:`\{x_i,y_i\}_{1\leq i \leq n}`
from __future__ import division, unicode_literals

from typing import List, Mapping

import matplotlib.pyplot as plt
import matplotlib.tri as mtri
from matplotlib.figure import Figure

from import DatasetPlot

[docs]class ZvsXY(DatasetPlot): """Plot surface z versus x,y.""" def _plot( self, properties, # type: Mapping x, # type: str y, # type: str z, # type: str x_comp=0, # type: int y_comp=0, # type: int z_comp=0, # type: int add_points=False, # type: bool ): # type: (...) -> List[Figure] """ Args: x: The name of the variable on the x-axis. y: The name of the variable on the y-axis. z: The name of the variable on the z-axis. x_comp: The component of x. y_comp: The component of y. z_comp: The component of z. add_points: If True, display samples over the surface plot. """ color = properties.get(self.COLOR) or "blue" colormap = properties.get(self.COLORMAP) or "Blues" x_data = self.dataset[x][x][:, x_comp] y_data = self.dataset[y][y][:, y_comp] z_data = self.dataset[z][z][:, z_comp] fig = plt.figure() axes = fig.add_subplot(1, 1, 1) grid = mtri.Triangulation(x_data, y_data) tcf = axes.tricontourf(grid, z_data, cmap=colormap) if add_points: axes.scatter(x_data, y_data, color=color) if self.dataset.sizes[x] == 1: axes.set_xlabel(self.xlabel or x) else: axes.set_xlabel(self.xlabel or "{}({})".format(x, x_comp)) if self.dataset.sizes[y] == 1: axes.set_ylabel(self.ylabel or y) else: axes.set_ylabel(self.ylabel or "{}({})".format(y, y_comp)) if self.dataset.sizes[z] == 1: axes.set_title(self.zlabel or z) else: axes.set_title(self.zlabel or "{}({})".format(z, z_comp)) fig.colorbar(tcf) return [fig]